huanzhang12 / RecurJac-and-CROWN
Reference implementations for RecurJac, CROWN, FastLin and FastLip (Neural Network verification and robustness certification algorithms) [Do not use this repo, use https://github.com/Verified-Intelligence/auto_LiRPA instead]
☆26Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for RecurJac-and-CROWN
- Fourth edition of VNN COMP (2023)☆16Updated last year
- Benchmark for LP-relaxed robustness verification of ReLU-networks☆40Updated 5 years ago
- β-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Verification☆30Updated 3 years ago
- Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTor…☆93Updated 3 years ago
- Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).☆22Updated 2 years ago
- Mixed integer programming for computing lipschitz constants of ReLU Networks☆17Updated last year
- The official repo for GCP-CROWN paper☆12Updated 2 years ago
- CROWN: A Neural Network Robustness Certification Algorithm for General Activation Functions (This repository is outdated; use https://git…☆16Updated 5 years ago
- This repository contains a simple implementation of Interval Bound Propagation (IBP) using TensorFlow: https://arxiv.org/abs/1810.12715☆153Updated 4 years ago
- Efficient Robustness Verification for ReLU networks (this repository is outdated, don't use; checkout our new implementation at https://g…☆30Updated 5 years ago
- [NeurIPS 2022] Code for paper "Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation"☆22Updated 11 months ago
- LipSDP - Lipschitz Estimation for Neural Networks☆62Updated 2 years ago
- CROWN: A Neural Network Verification Framework for Networks with General Activation Functions☆38Updated 5 years ago
- VNN Neural Network Verification Competition 2021☆37Updated 3 years ago
- ☆26Updated last year
- Code for Stability Training with Noise (STN)☆21Updated 3 years ago
- Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)☆45Updated 6 years ago
- Code of On L-p Robustness of Decision Stumps and Trees, ICML 2020☆10Updated 4 years ago
- Evaluating Robustness of Neural Networks with Mixed Integer Programming☆113Updated 3 months ago
- Code for paper "Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers"☆17Updated last year
- Benchmarks for the VNN Comp 2023☆14Updated 5 months ago
- Venus is a state-of-the-art sound and complete verification toolkit for Relu-based feed-forward neural networks. It can be used to check…☆13Updated 2 years ago
- Certifying Geometric Robustness of Neural Networks☆15Updated last year
- Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength☆37Updated 4 years ago
- [NeurIPS 2019] H. Chen*, H. Zhang*, S. Si, Y. Li, D. Boning and C.-J. Hsieh, Robustness Verification of Tree-based Models (*equal contrib…☆26Updated 5 years ago
- A united toolbox for running major robustness verification approaches for DNNs. [S&P 2023]☆88Updated last year
- PLANET: a Piece-wise LineAr feed-forward NEural network verification Tool☆43Updated 5 years ago
- OVAL framework for BaB-based Neural Network Verification☆13Updated 9 months ago
- [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.☆25Updated 3 months ago
- [NeurIPS 2021] Fast Certified Robust Training with Short Warmup☆23Updated last year